Microsoft DP-100 Korean : Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version)

DP-100 Korean pass collection

Exam Code: DP-100-KR

Exam Name: Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version)

Updated: Sep 13, 2026

Q & A: 528 Questions and Answers

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Step 2: Enrolling for the Instructor-Led Training Course

This is the most recommended way of preparing for the Microsoft DP-100 exam. Microsoft offers the official training course under the title “Designing and Implementing a Data Science Solution on Azure” to help the students build a solid knowledge base for the test. The training sessions are delivered to the individuals by the world-class professionals with plenty of experience in the field. So, the candidates get trained accordingly in the best way possible. Another advantage of taking the instructor-led course is that you have an opportunity to ask your questions and receive feedback whenever you face difficulties.

3. Models Management and Optimization (20-25%):

  • Usage of Automated Machine Learning for the creation of optimal models: This section requires your skills in retrieving the best models and getting data for Automated ML runs. It also covers competence in defining primary metrics, selecting pre-processing alternatives, and determining the algorithms to be searched. The candidates should be able to use the Automated Machine Learning from Azure ML SDK as well as Automated ML interface within Azure ML studios.
  • Usage of hyperdrive for the tuning of hyperparameters: This domain will evaluate the ability of the applicants to define search space, primary metrics, and early termination alternatives. It also expects their skills in sampling techniques selection and model discovery that require optimal hyper-parameter values.
  • Usage of model explainers for the interpretation of models: The learners have to demonstrate their competence in choosing model interpreters and generating the features of important data.
  • Models management: This objective focuses on trained model registration and monitoring of data drift and model usage.

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Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

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The candidates who want to take the Microsoft DP-100 exam are expected to have competence in its objectives. This means that they need to understand the scope of topics covered in this certification test. They are as follows:

1. Azure ML Workspace Set-Up (30-35%):

  • Data objects management within Azure ML workspace: The applicants should have competence in the creation and management of datasets, as well as maintenance and registration of datastores.
  • Experiment compute contexts management: The test takers must be able to create compute instances and compute targets for training and experiments. They have to know how to establish suitable compute specifications for training workloads.
  • Azure ML workspace creation: This area focuses on the students’ skills in creating Azure ML workspace, operating workspaces by using Azure ML studio, and configuring workspace settings.

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Microsoft DP-100 Korean Exam Syllabus Topics:

SectionObjectives
Explore and analyze data- Ingest and prepare data for modeling
- Perform exploratory data analysis
Optimize and manage models- Track experiments and manage model lifecycle
- Improve model performance
Train machine learning models- Train models using Azure Machine Learning
- Tune hyperparameters and evaluate models
Design and prepare a machine learning solution- Select appropriate Azure services for machine learning workloads
- Manage compute and data assets
- Plan and configure Azure Machine Learning workspace
Deploy and consume models- Monitor deployed models and endpoints
- Deploy models to endpoints

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